Conservative estimates suggest that there are tens of thousands of object classes in the visual world. This number may scale up by orders of magnitude considering more fine-grained classes. An outstanding issue is whether computers can recognize object classes while minimizing mistakes, which is a challenging task even to a knowledgeable human.
This seems elusive given that the state of the art performance on 10 K-way classification is only 16.7%. There is, however, a way to always be right: just report everything as an “entity,” which is not very informative.
In today's world, there are growing collections of images. With these collections of images, there is a further interest in classifying them so as to make them available for other purposes. For example, with properly classified images, searches could be performed on the content of the images rather than on text or other characteristics associated with them.
There is a need in the art for improved image classifiers. Moreover, there is a need for automatic image classification with reduced user input.